Aggregating human judgment probabilistic predictions of COVID-19 transmission, burden, and preventative measures

Allison Codi; Damon Luk; David Braun; Eva Chen; Juan Cambeiro; Luis Enrique Urtubey de C`esaris; Paolo Bocchini; Tamay Besiroglu; Thomas McAndrew

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Aggregating human judgment probabilistic predictions of COVID-19 transmission, burden, and preventative measures

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arxiv 2204.02466 v2 pith:Q7QMHEXP submitted 2022-04-05 stat.AP

Aggregating human judgment probabilistic predictions of COVID-19 transmission, burden, and preventative measures

Allison Codi , Damon Luk , David Braun , Juan Cambeiro , Tamay Besiroglu , Eva Chen , Luis Enrique Urtubey de C`esaris , Paolo Bocchini

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Thomas McAndrew

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Aggregated human judgment forecasts for COVID-19 targets of public health importance are accurate, often outperforming computational models. Our work shows aggregated human judgment forecasts for infectious agents are timely, accurate, and adaptable, and can be used as tool to aid public health decision making during outbreaks.

Aggregating human judgment probabilistic predictions of COVID-19 transmission, burden, and preventative measures

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